Generative AI for Phishing Detection
Applied Large Language Models (LLMs) to generate phishing emails and analyze their impact on cybersecurity defenses, providing insights for AI-driven security strategies.
Motivation
AI-generated phishing emails are increasingly sophisticated. This project aims to study these threats and evaluate detection methods to strengthen organizational security posture.
Tools & Technologies
- LangChain & Ollama for LLM integration
- Python for data processing and analysis
- Machine learning models (supervised classifiers)
- Visualization with matplotlib and seaborn
Methodology
- Generated phishing emails using LLMs with diverse personas to increase dataset variety.
- Created labeled datasets of AI-generated phishing emails.
- Trained supervised learning models to detect phishing content.
- Evaluated models using accuracy, precision, recall, and F1-score metrics.
Results & Key Takeaways
Enhanced detection of AI-generated phishing threats, showcasing the importance of LLMs in cybersecurity research. Learned methods to diversify training data and improve model performance using personas.